Postdoctoral Research Associate

Requisition Id 14907 

­­Overview:  

The Data and AI Systems Research Section/Workflow systems Group within the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is seeking a postdoctoral researcher with expertise in distributed intelligence, reasoning models, LLMs, workflow management, and distributed systems to contribute to the development of advanced decentralized intelligence techniques for scientific workflows deployed across heterogeneous computing resources. As a postdoctoral fellow at ORNL, you will join a dynamic team of researchers specializing in workflow management machine learning, distributed computing, and resource optimization leveraging the unique computational resources available at ORNL, including the Frontier supercomputer—the world's first exascale system.

 

In this role, you will collaborate with leading scientists to design and implement distributed intelligence solutions tailored for large-scale scientific workflows in DOE environments. Your work will be pivotal in advancing the state of the art in resilient infrastructure by developing more efficient and adaptive techniques that maintain robust performance guarantees while optimizing resource utilization across the computing continuum. Additionally, you will investigate innovative approaches to optimize the balance between performance and resilience, considering the complexities of heterogeneous resources and varying workflow requirements across diverse scientific applications.
 

The successful candidate will have the opportunity to use the computational power of the Frontier supercomputer to scale and validate these distributed intelligence algorithms, enabling breakthroughs in scientific research across DOE domains. The candidate will collaborate with DOE’s SWARM project (https://swarm-workflows.org/) members to advance robust, performant, and fault-tolerant execution of DOE scientific workflows. This position offers a unique opportunity to make significant contributions to both theoretical and applied aspects of distributed intelligence, driving advancements in resilient, adaptive AI systems on a global scale.

 

Responsibilities include, but not limited to:

• Develop novel decentralized methods that accommodate the diverse requirements of scientific workflows across the computing continuum.
• Develop and apply LLM-enabled swarm intelligence techniques for large-scale scientific workflows to advance research efforts across DOE scientific applications.
• Develop and apply distributed intelligence methods on heterogeneous computing resources from edge devices to leadership-class systems.
• Develop novel mathematically rigorous approaches to optimize the trade-off between performance and resilience especially in the context of large-scale distributed systems.
• Communicate and coordinate experimental results with other domain experts to facilitate collaboration.
• Present and report research results and publish scientific results in peer-reviewed journals or conferences.

 

Basic Qualifications:

• A PhD in Computer Science, Applied Mathematics, Computational Science, or related discipline completed within the last five years.
• Demonstrated hands-on experience and understanding of developing and applying distributed intelligence methods to workflows and resource management problems.
• Demonstrated research experience with AI and distributed systems techniques.

 

Preferred Qualifications:

• Knowledge of distributed intelligence algorithms and emergent behavior systems.
• Knowledge of distributed scientific workflow management and resour